# datatable.ifelse()¶

ifelse
(

An expression that chooses its value based on one or more conditions.

This is roughly equivalent to the following Python code:

result = value1 if condition1 else \ value2 if condition2 else \ ... else \ default 

For every row this function evaluates the smallest number of expressions necessary to get the result. Thus, it evaluates condition1, condition2, and so on until it finds the first condition that evaluates to True. It then computes and returns the corresponding value. If all conditions evaluate to False, then the default value is computed and returned.

Also, if any of the conditions produces NA then the result of the expression also becomes NA without evaluating any further conditions or values.

## Parameters¶

condition1
,
condition2
,
...
FExpr[bool]

Expressions each producing a single boolean column. These conditions will be evaluated in order until we find the one equal to True.

value1
,
value2
,
...
FExpr

Values that will be used when the corresponding condition evaluates to True. These must be single columns.

default
FExpr

Value that will be used when all conditions evaluate to False. This must be a single column.

return
FExpr

The resulting expression is a single column whose stype is the common stype for all value1, …, default columns.

## Notes¶

Changed in version 1.0.0

Earlier this function accepted a single condition only.

## Examples¶

### Single condition¶

Task: Create a new column Colour, where if Set is 'Z' then the value should be 'Green', else 'Red':

from datatable import dt, f, by, ifelse, update df = dt.Frame("""Type Set A Z B Z B X C Y""") df[:, update(Colour = ifelse(f.Set == "Z", # condition "Green", # if condition is True "Red")) # if condition is False ] df 
TypeSetColour
str32str32str32
0AZGreen
1BZGreen
2BXRed
3CYRed

### Multiple conditions¶

Task: Create new column value whose value is taken from columns a, b, or c – whichever is nonzero first:

df = dt.Frame({"a": [0,0,1,2], "b": [0,3,4,5], "c": [6,7,8,9]}) df 
abc
int32int32int32
0006
1037
2148
3259
df['value'] = ifelse(f.a > 0, f.a, # first condition and result f.b > 0, f.b, # second condition and result f.c) # default if no condition is True df 
abcvalue
int32int32int32int32
00066
10373
21481
32592